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Sunday, March 26, 2017

Machine learning: Should we be excited or fearful for our jobs? | Siliconrepublic.com

How machine learning can drive efficiency rather than drive people out of their jobs, insist Nicola Mortimer, head of business products, marketing and operations at Three Ireland.

Photo: vectorfusionart/Shutterstock

2017 will be a year of dramatic acceleration in the pace of
development of artificial intelligence (AI) and the internet of things
(IoT). Machine learning is predicted to be an integral part of more than
300m new smartphones sold this year. So, should we be excited or
fearful for our jobs?

It has been predicted that machine learning capabilities will be
present in more than 20pc of smartphones sold globally in 2017. With few
devices more ubiquitous in the developed world than the smartphone,
machines that learn will now be at the fingertips of a large percentage
of the population.What will the increasing development of machine learning, AI,
machine-to-machine (M2M) communication and IoT mean for business and
industry, and the people who work within them?

One of the important things to realise about the way machines learn,
and therefore develop intelligence, is that it is not a mysterious,
science-fiction process. Machine learning produces, in effect, nothing
more than glorified data crunchers.Machines that learn can learn only from the data they receive and
analyse. What makes them such quick learners and so apparently
intelligent is that – unlike humans – they can receive, absorb and
analyse all the relevant data in the world at incredibly high speed, and
then use it to inform the decisions they make.Importantly, for the development of true AI, these machines are now
also beginning to learn from the data and adapt their behaviour
accordingly. For example, at the simplest level, Google Translate now
adapts as it learns, to make its translations more accurate.At the other extreme, data gathered from the journeys of Tesla test
vehicles is uploaded to the cloud and made available to all Tesla
driverless cars. This means if a test vehicle has driven a stretch of
road, when another Tesla vehicle travels it for the first time, it will
know how to brake for a specific corner, which lane to take for a turn,
even what driving line to take to avoid a large pothole.Read more... Source: Siliconrepublic.com

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About Me

Hello, my name is Helge Scherlund and I am the Education Editor and Online Educator of this personal weblog and the founder of eLearning • Computer-Mediated Communication Center.
I have an education in the teaching adults and adult learning from Roskilde University, with Computer-Mediated Communication (CMC) and Human Resource Development (HRD) as specially studied subjects. I am the author of several articles and publications about the use of decision support tools, e-learning and computer-mediated communication. I am a member of The Danish Mathematical Society (DMF), The Danish Society for Theoretical Statistics (DSTS) and an individual member of the European Mathematical Society (EMS). Note: Comments published here are purely my own and do not reflect those of my current or future employers or other organizations.